Instructions to use Meanblock/JEV-CPU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Meanblock/JEV-CPU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Meanblock/JEV-CPU")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Meanblock/JEV-CPU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/jev-cpu-ui.png from Meanblock/JEV-CPU: direct link, hf CLI and curl.
- Browser
- Download file 252 kB
-
https://huggingface.co/Meanblock/JEV-CPU/resolve/main/assets/jev-cpu-ui.png
- Command line
-
hf download hf://Meanblock/JEV-CPU/assets/jev-cpu-ui.png
-
curl -L -o jev-cpu-ui.png https://huggingface.co/Meanblock/JEV-CPU/resolve/main/assets/jev-cpu-ui.png
252 kB

- Xet hash:
- 3f151f5fbaa3ba510eb337d4dd4773a8c5cd339723ab759463d801b230a95cd0
- Size of remote file:
- 252 kB
- SHA256:
- 287b01fcc9a63bd273ead3ccdc028c3537be11755b5e7ef4c93b6ccf527a5ae1
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